How to combine your enterprise data with generative AI.

With all the recent discussion about the use of artificial intelligence (AI) and large language models (LLMS) like ChatGPT, you may think that AI is a new phenomenon. But in fact, the US Department of Defense (DoD) has been investing in AI for more than 60 years.

Artificial intelligence (AI) apps are becoming increasingly crucial for individual customers and businesses alike. These apps bring many benefits, such as task automation, efficient analysis of large data sets, and data-informed decision-making, making AI-powered applications highly valuable. As a result, DevOps teams working on AI apps can’t afford poor performance.

Streaming analytics is an invaluable capability for organizations seeking to extract real-time insights from the log data they continuously generate through applications and cloud services. To help our community get started with streaming analytics on AWS, we published a piece last year called An Overview of Streaming Analytics in AWS for Logging Applications, where we covered all the basics.

This blog post dives into DevSecOps, the approach that blends DevOps, security, and operations into a cohesive security strategy. It focuses on the impact of DevSecOps on mobile software development and underscores the significance of prioritizing security from the get-go.

A lot of the buzz around AI focuses on its future potential. And we get it — we’re talking about a transformative technology that presents seemingly limitless possibilities. But an important aspect of this world-changing tech story that gets lost in the hype is understanding exactly what AI solutions are available for you and your team to employ right now, today.

By 2030, the value of the Generative AI (Gen AI) sector is expected to grow to USD 110.8 billion. GenAI is predicted to be responsible for 10% of all data generation by 2025, a stark increase from under 1% in 2021 – Gartner.